Electronic Health Records

This chapter introduces and reviews electronic health record (EHR) systems as essential core health information technology (IT). It describes current and potential future EHR functionality and discusses some of the challenges and controversies for these systems. EHRs include both traditional and newer capabilities for direct patient care and population health, as well as innovative Health IT working in concert with EHRs. Today’s EHR landscape includes challenges around EHR data entry, increased patient participation in EHR data entry, certified EHRs with increased inter-operability, and a number of regulatory requirements often leveraging EHRs.

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Overview of Electronic Health Records

Electronic Health Records and Patient Safety

Electronic Health Records: Origination, Adoption, and Progression

Notes

The terms “electronic health record” (EHR) and “electronic health record system” (EHRS or EHR system) are often used interchangeably, with no generally agreed upon distinction. The terms “electronic medical record” (EMR) and “electronic medical record system” (EMRS or EMR system) have also been used but many have moved towards using the term “health” versus “medical” as these systems are being used broadly across the continuum of care by a multitude of roles; again, the distinctions between EMR and EMRS are not generally agreed upon. The term “computer-based record system” has also been used in the past. In this chapter, and throughout the book, we will use the term “electronic health record”, with the acronyms “EHR” and “EHRs” to designate the singular and plural forms, respectively.

Certification of Health IT, Testing Process & Test Methods, 2015 Edition Test Method. 7 https://www.healthit.gov/topic/certification-ehrs/2015-edition-test-method (Accessed 6/4/2020).

Digital Imaging and Communications in Medicine, 7 https://www.dicomstandard.org/ (Accessed 6/4/2020).

Certification of Health IT, Testing Process & Test Methods, 2015 Edition Test Method. 7 https://www.healthit.gov/topic/certification-ehrs/2015-edition-test-method (Accessed 6/4/2020).

Logical Observation Identifiers Names and Codes (LOINC®) from Regenstrief. 7 http://loinc.org/ (Accessed 6/4/2020).

SNOMED Clinical Terms® (SNOMED CT®) Five-step briefing. 7 https://www.snomed.org/snomed-ct/ (Accessed 6/4/2020).

125 SNOMED CT groupers published as online supplement to open-access article above in reference #3. 7 https://www.thieme-connect.de/media/10.1055-s-00035026/201803/supmat/10-1055-s-0038-1668090-s180031ra.pdf (Accessed 6/4/2020).

Certification of Health IT, Testing Process & Test Methods, 2015 Edition Test Method. 2015 Edition Certification Regulations – 170.315(a) (1, 2, 3, 4): Computerized Provider Order Entry and Drug-drug and Drug-allergy checks for CPOE 7 https://www.healthit.gov/topic/certification-ehrs/2015-edition-test-method (Accessed 6/4/2020).

Certification of Health IT, Testing Process & Test Methods, 2015 Edition Test Method, Clinical Decision Support. 2015 Edition Certification Regulations - 170.315(a)(9): Clinical Decision Support 7 https://www.healthit.gov/test-method/clinical-decision-support-cds#ccg (Accessed 6/4/2020).

HL7 Version 3 Standard: Context Aware Knowledge Retrieval Application (“Infobutton”), Knowledge Request, Release 2. 7 http://www.hl7.org/implement/standards/product_brief.cfm?product_id=208 (Accessed 6/4/2020).

FHIRPath STU1 Release. [Internet]. 2019 [cited 01/29/2019]. Available from: 7 http://hl7.org/fhirpath/ (Accessed 6/4/2020).

Health Level 7. Clinical quality language (CQL) standard. [Internet]. 2018 [cited 01/29/2019]. Available from: 7 http://www.hl7.org/implement/standards/product_brief.cfm?product_id=400 (Accessed 6/4/2020).

Kentucky Health Information Exchange Frequently Asked Questions. 7 http://khie.ky.gov/Pages/faq.aspx?fc=010 (Accessed 6/4/2020).

We have included examples from various systems in this chapter, both developed by users and commercially available, to illustrate a portion of the functionality of EHRs currently in use.

References

• Anand, V., McKee, S., Dugan, T. M., & Downs, S. M. (2017). Leveraging electronic tablets for general pediatric care: A pilot study. Applied Clinical Informatics, 6(1), 1–15. Google Scholar
• Anand, V., Carroll, A. E., Biondich, P. G., Dugan, T. M., & Downs, S. M. (2018). Pediatric decision support using adapted Arden Syntax. Artificial Intelligence in Medicine, 92, 15–23. ArticlePubMedGoogle Scholar
• Arsoniadis, E. G., Skube, S. J., Bjerke, T. M., Jarabek, B., & Melton, G. B. (2017). Assessing provider-generated free-text quality in EHR-integrated handoff notes. Studies in Health Technology and Informatics, 245, 999–1003. PubMedGoogle Scholar
• Barnett, G. O. (1984). The application of computer-based medical-record systems in ambulatory practice. The New England Journal of Medicine, 310(25), 1643–1650. ArticleCASPubMedGoogle Scholar
• Barnett, G. O., Justice, N. S., Somand, M. E., et al. (1979). COSTAR – a computer-based medical information system for ambulatory care. Proceedings of the Institute of Electrical and Electronics Engineers (IEEE), 67, 1226–1237. Google Scholar
• Bates, D. W., Spell, N., Cullen, D. J., et al. (1997). The costs of adverse drug events in hospitalized patients. Journal of the American Medical Association, 277(4), 307–311. ArticleCASPubMedGoogle Scholar
• Bates, D. W., Evans, R. S., Murff, H., et al. (2003). Detecting adverse events using information technology. Journal of the American Medical Informatics Association: JAMIA, 10(2), 115–128. ArticlePubMedGoogle Scholar
• Bauer, D. T., Guerlain, S., & Brown, P. J. (2010). The design and evaluation of a graphical display for laboratory data. Journal of the American Medical Informatics Association: JAMIA, 17(4), 416–424. ArticlePubMedGoogle Scholar
• Bleich, H. L., Beckley, R. F., Horowitz, G. L., Jackson, J. D., Moody, E. S., Franklin, C., Goodman, S. R., McKay, M. W., Pope, R. A., Walden, T., et al. (1985). Clinical computing in a teaching hospital. The New England Journal of Medicine, 312(12), 756–764. ArticleCASPubMedGoogle Scholar
• ‘Brain’ to Store Medical Data. (1956, October 24). The New York Times. Google Scholar
• Brown, S. H., Lincoln, M. J., Groen, P. J., et al. (2003). VistA–U.S. Department of Veterans Affairs national-scale HIS. International Journal of Medical Informatics, 69(2–3), 135–156. ArticlePubMedGoogle Scholar
• Brown, S. H., Fischietti, L. F., Graham, G., Bates, J., et al. (2007). Use of electronic health records in disaster response: The experience of department of veterans affairs after hurricane Katrina. American Journal of Public Health, 97, S136–S141. ArticlePubMedPubMed CentralGoogle Scholar
• Brownstein, J. S., Sordo, M., Kohane, I. S., & Mandl, K. D. (2007). The tell-tale heart: Population-based surveillance reveals an association of rofecoxib and celecoxib with myocardial infarction. PLoS One, 2(9), e840. ArticlePubMedPubMed CentralCASGoogle Scholar
• Buchanan, J. (2017). Accelerating the benefits of the problem oriented medical record. Applied Clinical Informatics, 8(1), 180. PubMedPubMed CentralGoogle Scholar
• Buntin, M. B., Burke, M. F., Hoaglin, M. C., & Blumenthal, D. (2011). The benefits of health information technology: A review of the recent literature shows predominantly positive results. Health Affairs (Millwood), 30(3), 464–471. ArticleGoogle Scholar
• Burykin, A., Peck, T., & Buchman, T.G. (2011). Using “off-the-shelf” tools for terabyte-scale waveform recording in intensive care: computer system design, database description and lessons learned. In Computational Methods Programs Biomed. 103(3) (pp. 151–60). https://doi.org/10.1016/j.cmpb.2010.10.004.
• Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., Morton, S. C., et al. (2006). Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine, 144(10), 742–752. ArticlePubMedGoogle Scholar
• Cheung, N. T., Fung, K. W., Wong, K. C., et al. (2001). Medical informatics – the state of the art in the hospital authority. International Journal of Medical Informatics, 62, 113–119. Google Scholar
• Classen, D. C., Pestotnik, S. L., Evans, R. S., Lloyd, J. F., & Burke, J. P. (1997). Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. Journal of the American Medical Association, 277(4), 301–306. ArticleCASPubMedGoogle Scholar
• Clyne, B., Bradley, M. C., Hughes, C., et al. (2012). Electronic prescribing and other forms of technology to reduce inappropriate medication use and polypharmacy in older people: A review of current evidence. Clinical Geriatric Medicine, 28(2), 301–322. ArticleGoogle Scholar
• Coffey, R. (1979). How medical information systems affect costs: The El Camino experience. Washington, DC: Public Health Service. Publication DHEW-PHS-80-3626. Google Scholar
• Collen, M. F. (1969). Value of multiphasic health checkups. The New England Journal of Medicine, 280(19), 1072–1073. ArticleCASPubMedGoogle Scholar
• Collen, M. F. (1995). A history of medical informatics in the United States, 1950 to 1990. Bethesda: American Medical Informatics Association. Google Scholar
• Covell, D., Uman, G., & Manning, P. (1985). Information needs in office practice: Are they being met? Annals of Internal Medicine, 103, 596–599. ArticleCASPubMedGoogle Scholar
• Cusack, C. M., Hripcsak, G., Bloomrosen, M., Rosenbloom, T., Weaver, C., Wright, A., Vawdrey, D., Walker, J., & Mamykina, L. (2013). The future state of clinical data capture and documentation: A report from AMIA’s 2011 Policy Meeting. Journal of the American Medical Informatics Association: JAMIA, 20, 134–140. ArticlePubMedGoogle Scholar
• Damiani, G., Pinnarelli, L., Colosimo, S. C., Almiento, R., Sicuro, L., Galasso, R., Sommello, L., & Ricciardi, W. (2010). The effectiveness of computerized clinical guidelines in the process of care: A systematic review. BMC Health Services Research, 10, 2. ArticlePubMedPubMed CentralGoogle Scholar
• Damush, T. M., Weinberger, M., Clark, D. O., Tierney, W. M., Rao, J. K., Perkins, S. M., & Verel, K. (2002). Acute low back pain self management intervention for urban primary care patients: Rationale, design, and predictors of participation. Arthritis and Rheumatism, 47, 372–379. ArticlePubMedGoogle Scholar
• Davis, L. S., Collen, M. F., Rubin, F. L., & Van Brunt, E. E. (1968). Computer stored medical record. Computer Biomedical Research, 1, 452–469. ArticleCASGoogle Scholar
• Del Fiol, G., Huser, V., Strasberg, H. R., et al. (2012). Implementations of the HL7 context-aware knowledge retrieval (“infobutton”) standard: Challenges, strengths, limitations, and uptake. Journal of Biomedical Informatics, 45(4), 726–735. ArticlePubMedPubMed CentralGoogle Scholar
• Delvaux, N., Van Thienen, K., Heselmans, A., et al. (2017). The effects of computerized clinical decision support systems on laboratory test ordering: A systematic review. Archives of Pathology & Laboratory Medicine, 141(4), 585–595. ArticleGoogle Scholar
• Dexter, P. R., Perkins, S., Overhage, J. M., et al. (2001). A computerized reminder system to increase the use of preventive care for hospitalized patients. The New England Journal of Medicine, 345(13), 965–970. ArticleCASPubMedGoogle Scholar
• Dexter, P. R., Perkins, S. M., Maharry, K. S., Jones, K., & McDonald, C. J. (2004). Inpatient computer-based standing orders vs. physician reminders to increase influenza and pneumococcal vaccination rates. Journal of the American Medical Association, 292(19), 2366–2371. ArticleCASPubMedGoogle Scholar
• Downs, S. M., Biondich, P. G., Anand, V., Zore, M., & Carroll, A. E. (2006). Using Arden syntax and adaptive turnaround documents to evaluate clinical guidelines. In AMIA annual symposium proceedings, 2006 (pp. 214–218). Google Scholar
• Duke, J. D., Morea, J., Mamlin, B., Martin, D. K., Simonaitis, L., Takesue, B. Y., Dixon, B. E., & Dexter, P. R. (2014). Regenstrief Institute’s medical gopher: A next-generation homegrown electronic medical record system. International Journal of Medical Informatic, 83(3), 170–179. ArticleGoogle Scholar
• Duncan, R. G., Saperia, D., Dulbandzhyan, R., et al. (2001). Integrated web-based viewing and secure remote access to a clinical data repository and diverse clinical systems. In Proceedings of the AMIA fall symposium, 2001 (pp. 149–153). Google Scholar
• Earle, K. (2011). In people with poorly controlled hypertension, self-management including telemonitoring is more effective than usual care for reducing systolic blood pressure at 6 and 12 months. Evidence-Based Medicine, 16(1), 17–18. ArticlePubMedGoogle Scholar
• Edgar, E. P. (2009). Physician retention in Army Medical Department. Strategic Research Project, U.S. Army War College, Carlisle Barracks PA 17013–5050. Available at: http://handle.dtic.mil/100.2/ADA499087
• Evans, R. S., Pestotnik, S. L., Classen, D. C., Clemmer, T. P., Weaver, L. K., Orme, J. F., Lloyd, J. F., & Burke, J. P. (1998). A computer-assisted management program for antibiotics and other antinfective agents. The New England Journal of Medicine, 338(4), 232–238. ArticleCASPubMedGoogle Scholar
• Fafchamps, D., Young, C. Y., & Tang, P. C. (1991). Modelling work practices: Input to the design of a physician’s workstation. In Proceedings of the 15th annual symposium on computer applications in medical care (pp. 788–792). Washington, DC: CAMC. Google Scholar
• Ferranti, J. M., Musser, R. C., Kawamoto, K., & Hammond, W. E. (2006). The clinical document architecture and the continuity of care record: A critical analysis. Journal of the American Medical Informatics Association: JAMIA, 13(3), 245–252. ArticlePubMedGoogle Scholar
• Fitzmaurice, J. M., Adams, K., & Eisenberg, J. M. (2002). Three decades of research on computer applications in health care: Medical informatics support at the agency for healthcare research and quality. Journal of the American Medical Informatics Association: JAMIA, 9(2), 144–160. ArticlePubMedGoogle Scholar
• Flexner, A. (1910). Medical education in the united states and Canada: A report to the Carnegie foundation for the advancement of teaching. New York: The Carnegie Foundation for the Advancement of Teaching. OCLC 9795002. BookGoogle Scholar
• Fried, T. R., Niehoff, K. M., Street, R. L., et al. (2017). Effect of the tool to reduce inappropriate medications on medication communication and deprescribing. Journal of the American Geriatrics Society, 65(10), 2265–2271. ArticlePubMedPubMed CentralGoogle Scholar
• Fries, J. F. (1974). Alternatives in medical record formats. Medical Care, 12(10), 871–881. ArticleCASPubMedGoogle Scholar
• Frisse, M. E., King, J. K., Rice, W. B., et al. (2008). A regional health information exchange: Architecture and implementation. In American Medical Informatics Association annual symposium proceedings, 2008 (pp. 212–216). Google Scholar
• Frisse, M. E., Johnson, K., Nian, H., et al. (2011). The financial impact of health information exchange on emergency department care. Journal of the American Medical Informatics Association: JAMIA, 19(3), 328–333. ArticlePubMedGoogle Scholar
• Fry, E., & Schulte, F. (2019, March 18). Death by a thousand clicks: Where electronic health records went wrong. Fortune Magazine. Google Scholar
• Fung, K. W., Xu, J., Rosenbloom, S. T., et al. (2011). Testing three problem list terminologies in a simulated data entry environment. In American Medical Informatics Association annual symposium proceeds, 2011 (pp. 445–454). Google Scholar
• Gardner, R. L., Cooper, E., Haskell, J., et al. (2019). Physician stress and burnout: The impact of health information technology. JAMIA, 26(2), 106–114. PubMedGoogle Scholar
• Garg, A. X., Adhikari, N. K. J., McDonald, H., et al. (2005). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: A systematic review. Journal of the American Medical Association, 293(10), 1223–1238. ArticleCASPubMedGoogle Scholar
• Giuse, D. A., & Mickish, A. (1996). Increasing the availability of the computerized patient record. In Proceedings of the AMIA annual fall symposium, 1996 (pp. 633–637). Google Scholar
• Gottschalk, A., & Flocke, S. A. (2005). Time spent in face-to-face patient care and work outside the examination room. Annals of Family Medicine, 3(6), 488–493. ArticlePubMedPubMed CentralGoogle Scholar
• Green, B. B., Cook, A. J., Ralston, J. D., et al. (2008). Effectiveness of home blood pressure monitoring, web communication, and pharmacist care on hypertension control: A randomized controlled trial. Journal of the American Medical Association, 299(24), 2857–2867. ArticleCASPubMedGoogle Scholar
• Grossman, J. H., Barnett, G. O., Koepsell, T. D., Nesson, H. R., Dorsey, J. L., & Phillips, R. R. (1973). An automated medical record system. Journal of the American Medical Association, 224(12), 1616–1621. ArticleCASPubMedGoogle Scholar
• Gulacti, U., & Lok, U. (2017). Comparison of secure messaging application (WhatsApp) and standard telephone usage for consultations on Length of Stay in the ED. A prospective randomized controlled study. Applied Clinical Informatics, 8(3), 742–753. ArticlePubMedPubMed CentralGoogle Scholar
• Hagen, P. T., Turner, D., Daniels, L., & Joyce, D. (1998). Very large-scale distributed scanning solution for automated entry of patient information. TEPR Proceedings (Toward an ElectronicPatient Record), 1, 228–232. Google Scholar
• Halamka, J. D., & Safran, C. (1998). CareWeb: A web-based medical record for an integrated healthcare delivery system. In Proceedings of Medinfo 1998, Part 1 (pp. 36–39). Google Scholar
• Haynes, R. B. (Ed.). (2011). Computerized clinical decision support systems: How effective are they? [article collection] Implementation Science, 6, 87–108. Articles available at: http://www.implementationscience.com/series/CCDSS. Accessed 2 Jan 2012.
• Health IT Standards Committee. (2011). Recommendations to ONC on the assignment of code sets to clinical concepts [data elements] for use in quality measures. [Letter]. Retrieved from http://www.healthit.gov/sites/default/files/standards-certification/HITSC_CQMWG_VTF_Transmit_090911.pdf. Accessed 3 Jan 2012.
• Hirsch, J. S., Tanenbaum, J. S., Lipsky Gorman, S., Liu, C., Schmitz, E., Hashorva, D., Ervits, A., Vawdrey, D., Sturm, M., & Elhadad, N. (2015). HARVEST, a longitudinal patient record summarizer. Journal of the American Medical Informatics Association: JAMIA, 22, 263–274. ArticlePubMedGoogle Scholar
• Hollingsworth, J. C., Chisholm, C. D., Giles, B. K., Cordell, W. H., & Nelson, D. R. (1998). How do physicians and nurses spend their time in the emergency department? Annals of Emergency Medicine, 31, 87–91. ArticleCASPubMedGoogle Scholar
• Hripcsak, G., Cimino, J. J., & Sengupta, S. (1999). WebCIS: Large scale deployment of a web-based clinical information system. In Proceedings of the annual AMIA symposium, 1999 (pp. 804–808). Google Scholar
• Hunt, D. L., Haynes, R. B., et al. (1998). Effects of computer-based clinical decision support systems on physician performance and patient outcomes: A systematic review. JAMA : The Journal of the American Medical Association, 280(15), 1339–1346. Google Scholar
• Institute of Medicine Committee on Improving the Patient Record. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press. Available at: http://www.iom.edu/Reports/2001/Crossing-the-Quality-Chasm-A-New-Health-System-for-the-21st-Century.aspx. Accessed 2 Jan 2012.
• Janamanchi, B., Katsamakas, E., Raghupathi, W., & Gao, W. (2009). The state and profile of open source software projects in health and medical informatics. International Journal of Medical Informatics, 78(2009), 457–472. ArticlePubMedGoogle Scholar
• Johnson, S. B., Friedman, C., Cimino, J. J., Clark, T., Hripcsak, G., & Clayton, P. D. (1991). Conceptual data model for a central patient database. In Proceedings of the symposium on computer applications in medical care (pp. 381–385). Google Scholar
• Just, B. H., Marc, D., Munns, M., et al. (2016). Why patient matching is a challenge: Research on master patient index (MPI) data discrepancies in key identifying fields. Perspectives in Health Information Management, 13(Spring), 1e. PubMedPubMed CentralGoogle Scholar
• Khajouei, R., & Jaspers, M. W. (2010). The impact of CPOE medication systems’ design aspects on usability, workflow and medication orders: A systematic review. Methods of Information in Medicine, 49(1), 3–19. ArticleCASPubMedGoogle Scholar
• Kho, A., Zafar, A., & Tierney, W. (2007). Information technology in PBRNs: The Indiana University Medical Group Research Network (IUMG ResNet) experience. The Journal of the American Board of Family Medicine, 20(2), 196–203. ArticlePubMedGoogle Scholar
• Kohane, I. S. (2011). Using electronic health records to drive discovery in disease genomics. Nature Reviews Genetics, 12(6), 417–428. ArticleCASPubMedGoogle Scholar
• Koshy, S., Feustel, P. J., Hong, M., & Kogan, B. A. (2010). Scribes in an ambulatory urology practice: Patient and physician satisfaction. Journal of Urology, 184(1), 258–262. ArticleGoogle Scholar
• Kuhn, I. M., Wiederhold, G., Rodnick, J.E., et al. (1984). Automated ambulatory medical record systems in the U.S. In Blum, B. (Ed.), Information systems for patient care (pp.199–217), New York: Springer. Original 1982 report available at: http://infolab.stanford.edu/TR/CS-TR-82-928.html. Accessed 2 Jan 2012.
• Lamb, A. (1955). The Presbyterian Hospital and the Columbia-Presbyterian Medical Center, 1868–1943: A history of a great medical adventure. New York: Columbia University Press. Google Scholar
• Larsen, R. A., Evans, R. S., Burke, J. P., Pestotnik, S. L., Gardner, R. M., & Classen, D. C. (1989). Improved perioperative antibiotic use and reduced surgical wound infections through use of computer decision analysis. Infection Control and Hospital Epidemiology, 10(7), 316–320. ArticleCASPubMedGoogle Scholar
• Lau, F., Kuziemsky, C., Price, M., & Gardner, J. (2010). A review on systematic reviews of health information system studies. Journal of the American Medical Informatics Association: JAMIA, 17(6), 637–645. ArticlePubMedGoogle Scholar
• Longhurst, C. A., Harrington, R. A., & Shah, N. H. (2014). A ‘green button’ for using aggregate patient data at the point of care. Health Affairs, 33(7), 1229–1235. ArticlePubMedGoogle Scholar
• Major, K., Shabot, M. M., & Cunneen, S. (2002). Wireless clinical alerts and patient outcomes in the surgical intensive care unit. American Surgery, 68, 1057–1060. ArticleGoogle Scholar
• Mamlin BW, Overhage JM, Tierney WM, Dexter PR, McDonald CJ. Clinical Decision Support Within the Regenstrief Medical Record System. Book chapter - Clinical Decision Support Systems -Theory and Practice - Series: Health Informatics, Berner, Eta S. (Ed.) 2nd ed., 2007, 190–21. Google Scholar
• Mandel, J. C., Kreda, D. A., Mandl, K. D., Kohane, I. S., & Ramoni, R. B. (2016). SMART on FHIR: A standards-based, interoperable apps platform for electronic health records. Journal of the American Medical Informatics Association, 23(5), 899–908. ArticlePubMedPubMed CentralGoogle Scholar
• Mandl, K. D., Gottlieb, D., & Ellis, A. (2019). Beyond one-off integrations: A commercial, substitutable, reusable, standards-based, electronic health record–connected app. Journal of Medical Internet Research, 21(2), e12902. https://doi.org/10.2196/12902. ArticlePubMedPubMed CentralGoogle Scholar
• McDonald, C. J. (1973, November) The clinical automaton—An ambulatory care record with control capabilities. In Proceedings of the IEEE Conf Cyber Soc. (pp. 27–31). Google Scholar
• McDonald, C. J. (1976). Protocol-based computer reminders. The quality of care and the non-perfectibility of man. The New England Journal of Medicine, 295(24), 1351–1355. https://doi.org/10.1056/NEJM197612092952405. ArticleCASPubMedGoogle Scholar
• McDonald, C. J., Bhargava, B., & Jeris, D. W. (1975). A clinical information system (CIS) for ambulatory care. In Proceedings AFIPS national computing conference, Anaheim. Google Scholar
• McDonald, C. J., Overhage, J. M., Tierney, W. M., et al. (1999). The regenstrief medical record system: A quarter century experience. International Journal of Medical Informatics, 54(3), 225–253. ArticleCASPubMedGoogle Scholar
• McDonald, C. J., Huff, S. M., Suico, J. G., et al. (2003). LOINC, a universal standard for identifying laboratory observations: A 5-year update. Clinical Chemistry, 49(4), 624–633. ArticleCASPubMedGoogle Scholar
• McDonald, C. J., Overhage, J. M., Barnes, M., Schadow, G., Blevins, L., Dexter, P. R., & Mamlin, B. W. (2005). The Indiana network for patient care: A working local health information infrastructure (LHII). Health Affairs (Millwood), 24(5), 1214–1220. ArticleGoogle Scholar
• McDonald CJ, Callaghan FM, Weissman A, Goodwin RM, Mundkur M, Kuhn T. Use of Internist’s Free Time by Ambulatory Care Electronic Medical Record Systems. JAMA Intern Med. 2014;174(11):1860–1863. https://doi.org/10.1001/jamainternmed.2014.4506.
• McPhee, S. J., Bird, J. A., Fordham, D., Rodnick, J. E., & Osborn, E. H. (1991). Promoting cancer prevention activities by primary care physicians: Results of a randomized, controlled trial. Journal of the American Medical Association, 266(4), 538–544. ArticleCASPubMedGoogle Scholar
• Melton, L. J., 3rd. (1996). History of the Rochester epidemiology project. Mayo Clinic Proceedings, 71, 266–274. ArticlePubMedGoogle Scholar
• Miller, R. A., & Gardner, R. M. (1997). Recommendations for responsible monitoring and regulation of clinical software systems. Journal of the American Medical Informatics Association: JAMIA, 4, 442–457. ArticleCASPubMedGoogle Scholar
• Miller, R. A., Gardner, R. M., Johnson, K. B., & Hripcsak, G. (2005a). Clinical decision support and electronic prescribing systems: A time for responsible thought and action. Journal of the American Medical Informatics Association: JAMIA, 12(4), 403–409. ArticlePubMedGoogle Scholar
• Miller, R. A., Waitman, L. R., Chen, S., & Rosenbloom, S. T. (2005b). The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt. Journal of Biomedical Informatics, 38(6), 469–485. ArticlePubMedPubMed CentralGoogle Scholar
• Misra-Hebert, A. D., et al. (2016, March). Medical scribes: How do their notes stack up? Journal of Family Practice, 155+. Gale Academic Onefile, Accessed 14 Oct 2019. Google Scholar
• Muth, C., Ulhmann, L., Haefeli, W. E., et al. (2018). Effectiveness of a complex intervention on Prioritising Multimedication in Multimorbidity (PRIMUM) in primary care: Results of a pragmatics cluster randomised controlled trial. BMJ Open, 8(2), e017740. ArticlePubMedPubMed CentralGoogle Scholar
• Nadkarni, P. M., Ohno-Machado, L., & Chapman, W. W. (2011). Natural language processing: An introduction. Journal of the American Medical Informatics Association: JAMIA, 18(5), 544–551. ArticlePubMedGoogle Scholar
• National Committee on Vital and Health Statistics. (2001). Information for health: A strategy for building the National Health Information Infrastructure. Report and recommendations from the National Committee on Vital and Health Statistics. Available at http://www.ncvhs.hhs.gov/nhiilayo.pdf. Accessed 17 Dec 2012.
• Nebeker, J. R., Hoffman, J. M., Weir, C. R., Bennett, C. L., & Hurdle, J. F. (2005). High rates of adverse drug events in a highly computerized hospital. Archives of Internal Medicine, 165(10), 1111–1116. ArticlePubMedGoogle Scholar
• Openchowski, M. W. (1925). The effect of the unit record system and improved organization on hospital economy and efficiency. Archives of Surgery, 10(3), 925–934. ArticleGoogle Scholar
• Overhage JM, Tierney WM, Zhou XH, McDonald CJ. A Randomized Trial of “Corollary Orders” to Prevent Errors of Omission. J Am Med Inform Assoc. 1997;4(5):364–75. PMID: 9292842. Google Scholar
• Ozdas, A., Miller, R. A., & Waitman, L. R. (2008). Care Provider Order Entry (CPOE): A perspective on factors leading to success or to failure. Yearbook of Medical Informatics, 2007, 128–137. Review. Erratum in: Yearbook of Medical Informatics, 2008, 19. Google Scholar
• Parshuram, C. S., Dryden-Palmer, K., Farrell, C., et al. (2018). Effect of a pediatric early warning system on all-cause mortality in hospitalized pediatric patients: The EPOCH randomized clinical trial. JAMA, 319(10), 1002–1012. ArticlePubMedPubMed CentralGoogle Scholar
• Pestotnik, S. L. (2005). Expert clinical decision support systems to enhance antimicrobial stewardship programs: Insights from the Society of Infectious Diseases Pharmacists. Pharmacotherapy, 25(8), 1116–1125. ArticlePubMedGoogle Scholar
• Phansalkar, S., Desai, A. A., Bell, D., et al. (2012a). High-priority drug-drug interactions for use in electronic health records. Journal of the American Medical Informatics Association: JAMIA, 19(5), 735–743. ArticlePubMedGoogle Scholar
• Phansalkar, S., van der Sijs, H., Tucker, A. D., et al. (2012b). Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records. Journal of the American Medical Informatics Association: JAMIA, 20(3), 489–493. ArticlePubMedGoogle Scholar
• Poissant, L., Pereira, J., Tamblyn, R., & Kawasumi, Y. (2005, September 1). The impact of electronic health records on time efficiency of physicians and nurses: A systematic review. Journal of the American Medical Informatics Association, 12(5), 505–516. ArticlePubMedPubMed CentralGoogle Scholar
• Poon, E. G., Kuperman, G. J., Fiskio, J., & Bates, D. W. (2002). Real-time notification of laboratory data requested by users through alphanumeric pagers. Journal of the American Medical Informatics Association: JAMIA, 9, 217–222. ArticlePubMedGoogle Scholar
• Pryor, T.A. (1988) The HELP medical record system. In MD Computing. 5(5). (pp. 22–33). PMID: 3231033. Google Scholar
• Przvbvlo, J. A., Wang, A., Loftus, P., et al. (2014). Smarter hospital communication: Secure smartphone text messaging improves provider satisfaction and perception of efficacy, workflow. Journal of Hospital Medicine, 9(9), 573–578. ArticleGoogle Scholar
• Ranta, A., Dovey, S., Weatherall, M., et al. (2015). Cluster randomized controlled trial of TIA electronic decision support in primary care. Neurology, 84(15), 1545–1551. ArticlePubMedGoogle Scholar
• Reiser, S. (1991). The clinical record in medicine. Part 1: Learning from cases. Annals of Internal Medicine, 114(10), 902–907. ArticleCASPubMedGoogle Scholar
• Rief, J. J., Hamm, M. E., Zickmund, S. L., et al. (2017). Using health information technology to Foster engagement: Patients’ experiences with an active patient health record. Health Communications, 32(3), 310–319. ArticleGoogle Scholar
• Rind, D. M., Safran, C., Phillips, R. S., Wang, Q., Calkins, D. R., Delbanco, T. L., Bleich, H. L., & Slack, W. V. (1994). Effect of computer-based alerts on the treatment and outcomes of hospitalized patients. Archives of Internal Medicine, 154(13), 1511–1517. ArticleCASPubMedGoogle Scholar
• Roden, D. M., Pulley, J. M., Basford, M. A., Bernard, G. R., Clayton, E. W., Balser, J. R., & Masys, D. R. (2008, September). Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clinical Pharmacology and Therapeutics, 84(3), 362–369. ArticleCASPubMedPubMed CentralGoogle Scholar
• Romano, M. J., & Stafford, R. S. (2011). Electronic health records and clinical decision support systems: Impact on national ambulatory care quality. Archives of Internal Medicine, 171(10), 897–903. ArticlePubMedPubMed CentralGoogle Scholar
• Rosenbloom, S. T., Geissbuhler, A. J., Dupont, W. D., Giuse, D. A., Talbert, D. A., Tierney, W. M., Plummer, W. D., Stead, W. W., & Miller, R. A. (2005). Effect of CPOE user interface design on user-initiated access to educational and patient information during clinical care. Journal of the American Medical Informatics Association: JAMIA, 12(4), 458–473. ArticlePubMedGoogle Scholar
• Samantaray, R., Njoku, V. O., Brunner, J. W., Raghavan, V., Kendall, M. L., & Shih, S. C. (2011). Promoting electronic health record adoption among small independent primary care practices. The American Journal of Managed Care, 17(5), 353–358. PubMedGoogle Scholar
• Schedlbauer, A., Prasad, V., Mulvaney, C., Phansalkar, S., Stanton, W., Bates, D. W., & Avery, A. J. (2009). What evidence supports the use of computerized alerts and prompts to improve clinicians’ prescribing behavior? Journal of the American Medical Informatics Association: JAMIA, 16(4), 531–538. ArticlePubMedGoogle Scholar
• Schultz, J. R., Cantrill, S. V., & Morgan, K. G. (1971). AFIPS Conference Proceedings, 38, 239–264. Google Scholar
• Schwartz, R. J., Weiss, K. M., & Buchanan, A. V. (1985). Error control in medical data. MD Computing, 2(2), 19–25. CASPubMedGoogle Scholar
• Sherifali, D., Greb, J. L., Amirthavasar, G., Hunt, D., Haynes, R. B., Harper, W., Holbrook, A., Capes, S., Goeree, R., O’Reilly, D., Pullenayegum, E., & Gerstein, H. C. (2011). Effect of computer-generated tailored feedback on glycemic control in people with diabetes in the community: A randomized controlled trial. Diabetes Care, 34(8), 1794–1798. ArticlePubMedPubMed CentralGoogle Scholar
• Simborg, D. W., & Whiting-O’Keefe, Q. E. III. (1981, November 4). The Physician’s Office and Group practice—ambulatory medical record systems: A automated medical record systems: Summary time oriented record (STOR)—a progress report. In Proceedings of the annual symposium on computer application in Medical Care (p. 100). Google Scholar
• Simonaitis, L., Belsito, A., Warvel, J., Hui, S., & McDonald, C. J. (2006). Extensible stylesheet language formatting objects (XSL-FO): A tool to transform patient data into attractive clinical reports. In AMIA annual symposium proceedings, 2006 (pp. 719–723). Google Scholar
• Sinsky, C., Colligan, L., Li, L., Prgomet, M., Reynolds, S., Goeders, L., Westbrook, J., Tutty, M., & Blike, G. (2016). Allocation of physician time in ambulatory practice: A time and motion study in 4 specialties. Annals of Internal Medicine, 2165(11), 753–760. ArticleGoogle Scholar
• Slack, W. V., & Bleich, H. L. (1999). The CCC system in two teaching hospitals: A progress report. International Journal of Medical Informatics, 54(3), 183–196. ArticleCASPubMedGoogle Scholar
• Starren, J., & Johnson, S. B. (2000). An object-oriented taxonomy of medical data presentations. Journal of the American Medical Informatics Association: JAMIA, 7(1), 1–20. ArticleCASPubMedGoogle Scholar
• Stead, W.W., Brame, R.G., Hammond, W.E., et. al. (1977). A computerized obstetric medical record. In Obstetrics & Gynecology. 49(4). (pp. 502-9). PMID 854253. Google Scholar
• Stead, W. W., & Hammond, W. E. (1988). Computer-based medical records: The centerpiece of TMR. MD Computing, 5(5), 48–62. CASPubMedGoogle Scholar
• Stein, D. M., Vawdrey, D. K., Stetson, P. D., & Bakken, S. (2010). An analysis of team checklists in physician signout notes. In American Medical Informatics Association annual symposium proceedings (pp. 767–771). Google Scholar
• Strom, B. L., Schinnar, R., Aberra, F., Bilker, W., Hennessy, S., Leonard, C. E., & Pifer, E. (2010). Unintended effects of a computerized physician order entry nearly hard-stop alert to prevent a drug interaction: A randomized controlled trial. Archives of Internal Medicine, 170(17), 1578–1583. ArticlePubMedGoogle Scholar
• Syzdykkova, A., Malta, A., Zolfo, M., et al. (2017). Open-source electronic health record systems for low-resource settings: Systematic review. JMIR Medical Informatics, 5(4), e44. ArticleGoogle Scholar
• Tajmir, S., Raja, A. S., Ip, I. K., et al. (2017). Impact of clinical decision support on radiography for acute ankle injuries: A randomized trial. The Western Journal of Emergency Medicine, 18(3), 487–495. ArticlePubMedPubMed CentralGoogle Scholar
• Tang, P. C. (2003). Key capabilities of an electronic health record system (letter report). Committee on Data Standards for Patient Safety. Board on Health Care Services, Institute of Medicine. Google Scholar
• Tang, P. C., & Patel, V. L. (1994). Major issues in user interface design for health professional workstations: Summary and recommendations. International Journal of Biomedical Computing, 34(104), 130–148. Google Scholar
• Tang, P. C., Annevelink, J., Suermondt, H. J., & Young, C. Y. (1994a). Semantic integration in a physician’s workstation. International Journal of Bio-Medical Computing, 35(1), 47–60. ArticleCASPubMedGoogle Scholar
• Tang, P. C., Fafchamps, D., & Shortliffe, E. H. (1994b). Traditional medical records as a source of clinical data in the outpatient setting. In Proceedings of the annual symposium computer applications in Medical Care (pp. 575–579). Google Scholar
• Tang, P. C., Marquardt, W. C., Boggs, B., et al. (1999). NetReach: Building a clinical infrastructure for the enterprise. In J. M. Overhage (Ed.), Fourth annual proceedings of the Davies CPR recognition symposium (pp. 25–68). Chicago: McGraw-Hill. Google Scholar
• Tang, P. C., Ralston, M., Arrigotti, M. F., Qureshi, L., & Graham, J. (2007). Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: Implications for performance measures. Journal of the American Medical Informatics Association: JAMIA, 14, 10–15. ArticleCASPubMedGoogle Scholar
• Teich, J. M., Glaser, J. P., Beckley, R. F., et al. (1999). The Brigham integrated computing system (BICS): Advanced clinical systems in an academic hospital environment. International Journal of Medical Informatics, 54(3), 197–208. ArticleCASPubMedGoogle Scholar
• Teich, J. M., Merchia, P. R., Schmiz, J. L., et al. (2000). Effects of computerized physician order entry on prescribing practices. Archives of Internal Medicine, 160(18), 2741–2747. ArticleCASPubMedGoogle Scholar
• Tierney, W. M., Miller, M. E., Overhage, J. M., & McDonald, C. J. (1993). Physician inpatient order writing on microcomputer workstations: Effects on resource utilization. Journal of the American Medical Association, 269(3), 379–383. ArticleCASPubMedGoogle Scholar
• Tufte, E. (2006). Beautiful evidence. Cheshire: Graphics Press. ISBN 978-0-9613921-7-8.. Google Scholar
• Vigoda, M. M., & Lubarsky, D. A. (2006). Failure to recognize loss of incoming data in an anesthesia record-keeping system may have increased medical liability. Anesthesia and Analgesia, 102, 1798–1802. ArticlePubMedGoogle Scholar
• Vreeman, D. J., McDonald, C. J., & Huff, S. M. (2010). Representing patient assessments in LOINC®. In American Medical Informatics Association annual symposium proceedings, 2010 (pp. 832–836). Google Scholar
• Wang, A.Y., Sable, J.H., & Spackman, K.A. (2002). The SNOMED clinical terms development process: refinement and analysis of content. In American Medical Informatics Association annual symposium proceedings, 2002 (pp. 845–9). PMCID: PMC2244575. Google Scholar
• Warner, H. R. (1972). A computer-based patient information system for patient care. In G. A. Bekey & M. D. Schwartz (Eds.), Hospital information systems (pp. 293–332). New York: Marcel Dekker. Google Scholar
• Weir, C. R., Hammond, K. W., Embi, P. J., et al. (2011). An exploration of the impact of computerized patient documentation on clinical collaboration. International Journal of Medical Informatics, 80(8), e62–e71. ArticlePubMedGoogle Scholar
• Willett, D. L., Kannan, V., Chu, L., Buchanan, J. R., Velasco, F. T., Clark, J. D., Fish, J. S., Ortuzar, A. R., Youngblood, J. E., Bhat, D. G., & Basit, M. A. (2018). SNOMET CT concept hierarching for sharing definitions of clinical conditions using electronic health record data. Applied Clinical Informatics, 9(3), 667. ArticlePubMedPubMed CentralGoogle Scholar
• Wrenn, J. O., Stein, D. M., Bakken, S., & Stetson, P. D. (2010). Quantifying clinical narrative redundancy in an electronic health record. Journal of the American Medical Informatics Association: JAMIA, 17(1), 49–53. ArticlePubMedGoogle Scholar
• Zech, J., Husk, G., Moore, T., et al. (2016). Measuring the degree of unmatched patient records in a health information exchange using exact matching. Applied Clinical Informatics, 7(2), 330–340. ArticlePubMedPubMed CentralGoogle Scholar
• Zhang, R., Pakhomov, S. V., Lee, J. T., & Melton, G. B. (2014). Using language models to identify relevant new information in inpatient clinical notes. In American Medical Informatics Association annual symposium proceedings (pp. 1268–1276). Google Scholar

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Authors and Affiliations

1. Department of Surgery and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA Genevieve B. Melton
2. Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA Clement J. McDonald
3. Clinical Excellence Research Center, Stanford University,, Stanford, CA, USA Paul C. Tang
4. Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA George Hripcsak

1. Genevieve B. Melton

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1. Biomedical Informatics, Columbia University, New York, NY, USA Edward H. Shortliffe
2. Informatics Institute, University of Alabama at Birmingham, Birmingham, AL, USA James J. Cimino

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Melton, G.B., McDonald, C.J., Tang, P.C., Hripcsak, G. (2021). Electronic Health Records. In: Shortliffe, E.H., Cimino, J.J. (eds) Biomedical Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-58721-5_14

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